Instructions to use sshleifer/student_xsum_12_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_xsum_12_2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_xsum_12_2") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_xsum_12_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4ff391e919d017357f7f66fab81bd9d779dd1598bb6cb934d55e07eef6c7d0c
- Size of remote file:
- 954 MB
- SHA256:
- 265ce699645a6116d0f6f0f1233325b6b588b0d3a5c8331395b278d200a44d18
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